We present the first general study on the effect of Möbius transformations on the eigenvalue condition numbers and backward errors of approximate eigenpairs of polynomial eigenvalue problems (PEPs). By usingthe homogeneous formulation of PEPs, we are able to obtain two clear andsimple results. First, we show that if the matrix inducing the Möbius transformation is well-conditioned, then such transformation approximately preservesthe eigenvalue condition numbers and backward errors when they are definedwith respect to perturbations of the matrix polynomial which are small relativeto the norm of the whole polynomial. However, if the perturbations in eachcoefficient of the matrix polynomial are small relative to the norm of that coefficient, t...
It is commonplace in many application domains to utilize polynomial eigenvalue problems to model the...
Eigenvalue and eigenpair backward errors are computed for matrix pencils arising in optimal control....
It is commonplace in many application domains to utilize polynomial eigenvalue problems to model the...
We present the first general study on the effect of Möbius transformations on the eigenvalue conditi...
Mención Internacional en el título de doctorThis PhD thesis belongs to the areas of Matrix Analysis ...
Mención Internacional en el título de doctorThis PhD thesis belongs to the areas of Matrix Analysis ...
Mención Internacional en el título de doctorThis PhD thesis belongs to the areas of Matrix Analysis ...
In this thesis, we consider polynomial eigenvalue problems. We extend results on eigenvalue and eige...
The most widely used approach for solving the polynomial eigenvalue problem $P(\lambda)x = \bigl(\su...
The standard way to solve polynomial eigenvalue problems is through linearizations. The family of F...
The standard way to solve polynomial eigenvalue problems is through linearizations. The family of F...
Minimal structured perturbations are constructed such that an approximate eigenpair of a nonlinear e...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
It is commonplace in many application domains to utilize polynomial eigenvalue problems to model the...
Eigenvalue and eigenpair backward errors are computed for matrix pencils arising in optimal control....
It is commonplace in many application domains to utilize polynomial eigenvalue problems to model the...
We present the first general study on the effect of Möbius transformations on the eigenvalue conditi...
Mención Internacional en el título de doctorThis PhD thesis belongs to the areas of Matrix Analysis ...
Mención Internacional en el título de doctorThis PhD thesis belongs to the areas of Matrix Analysis ...
Mención Internacional en el título de doctorThis PhD thesis belongs to the areas of Matrix Analysis ...
In this thesis, we consider polynomial eigenvalue problems. We extend results on eigenvalue and eige...
The most widely used approach for solving the polynomial eigenvalue problem $P(\lambda)x = \bigl(\su...
The standard way to solve polynomial eigenvalue problems is through linearizations. The family of F...
The standard way to solve polynomial eigenvalue problems is through linearizations. The family of F...
Minimal structured perturbations are constructed such that an approximate eigenpair of a nonlinear e...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
The standard way of solving numerically a polynomial eigenvalue problem (PEP) is to use a linearizat...
It is commonplace in many application domains to utilize polynomial eigenvalue problems to model the...
Eigenvalue and eigenpair backward errors are computed for matrix pencils arising in optimal control....
It is commonplace in many application domains to utilize polynomial eigenvalue problems to model the...